build: bump docker base images and install docs to v0.22.0

Update Dockerfiles, quickstart, and installation guides to reference
vLLM v0.22.0 (CUDA 12.9, ROCm 7.2.2) instead of v0.20.0/v0.21.0.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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hsliuandClaude Opus 4.7 committed 2026-06-09 06:13:06 +08:00
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@@ -45,7 +45,7 @@ If you do not need to modify source code of vLLM, you can directly install the s
uv pip install vllm==0.22.0 --torch-backend=auto
```
The 0.22.0 release of vLLM ships CUDA 13.0-compatible binaries by default. If you need a different CUDA variant or want to reuse an existing PyTorch installation, build vLLM from source instead.
The 0.22.0 release of vLLM ships CUDA 12.9-compatible binaries by default. If you need a different CUDA variant or want to reuse an existing PyTorch installation, build vLLM from source instead.
#### Installation of vLLM-Omni
Since vllm-omni is rapidly evolving, it's recommended to install it from source
@@ -70,8 +70,8 @@ git checkout v0.22.0
```
Set up environment variables to get pre-built wheels. If there are internet problems, just download the whl file manually. And set `VLLM_PRECOMPILED_WHEEL_LOCATION` as your local absolute path of whl file.
```bash
#For CUDA 13.0 (the default for v0.22.0; the wheel filename has no `+cu130` suffix)
export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.22.0/vllm-0.22.0-cp38-abi3-manylinux_2_35_x86_64.whl
#For CUDA 12.9 (the default for v0.22.0; the wheel filename has no `+cu129` suffix)
export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.22.0/vllm-0.22.0-cp38-abi3-manylinux_2_28_x86_64.whl
```
Install vllm with command below (If you have no existing PyTorch).
```bash